Day 2: Monday, October 21st
7:30 am - 8:00 am Breakfast
8:00 am - 8:05 am Chairperson's Opening Remarks
8:35 am - 8:50 am Creating the Data Driven Operating Model of the Future
In order to drive the transformation required to remain competitive and thrive in the future there must be full, enterprise wide adoption of a data driven culture. The obstacles vary by organization however success requires a sound operating model that creates engagement and support with business leaders.
Hear strategies for:
- Centralizing the Strategy, Vision and Thinking
- Helping the Business Understand How to Leverage Capabilities
- Defining Data & Analytics as a Capability Rather Than a Function or Discipline
- Establishing the optimal hub & spoke capability model
Gary BarrManaging Director, Global Chief Data Officer
8:50 am - 9:15 am Follow on Panel Discussion: Designing the Data Driven Operating Model of the Future
Following Gary Barr's opening thoughts on the subject he will be joined by other practitioners in a lively panel discussion to offer additional perspectives on this very important topic. Following the panel discussion the floor will be open for an extended Q&A session.
Gary BarrManaging Director, Global Chief Data Officer
Simon DennisonVice President Strategy, Data and Analytics
Sun Life Financial
9:15 am - 9:45 am Applying Artificial Intelligence to Drive Dynamic Pricing
As customers become more comfortable and accepting of supply and demand based pricing through ride sharing or hotel booking experiences they are beginning to expect the same type of dynamic pricing in other purchases. AI is making that possible in many other areas. Mastering how to apply this to your customer is a game changer in the customer journey, efficiency and, revenue maximization.
- How to achieve dynamic offerings
- How to maximize revenue in real time
- How to quickly react to customer requirements
9:45 am - 10:15 am Harnessing Information from Data - Challenges and Opportunities
Institutions today are more focused than ever on harnessing the power of their data to provide a competitive advantage. This has its challenges but also presents several opportunities. This talk looks at the approach to mastering corporate data from defining the business problem to measuring success.
• Moving beyond problem to identify implications
• Developing a strategic approach
• Identifying talent & infrastructure requirements
• Defining the metrics for success
Lovell HodgeVice President of Data and Adaptive Intelligence
10:15 am - 10:30 am Networking Break
10:30 am - 11:00 am Business Meetings
11:00 am - 11:30 am Business Meetings
11:30 am - 12:00 pm Business Meetings
Masterclass12:00 pm - 12:40 pm Delivering Value to Your Customers With an Effective Customer Data Platform
Your customers expect your company to be a single entity, not a series of siloed employees and departments. Utilizing a CDP simply to market to your customers isn’t good enough. A well designed and deployed CDP will allow your company to:
- Create a true sense of relationship with your customers
- Allow employees from all departments efficiently and effectively deliver value to customers
- Ensure that every customer interaction is a positive representation of your brand
Masterclass12:00 pm - 12:40 pm Merging Disparate Data Sources into a Primary Data Hub
As your organization grows through acquisitions, new office launches, and/or global expansion, your organizational data grows, as well. As a result, managing multiple data sources and consolidating them into one useable data hub can be an ongoing challenge for Data & Analytics leaders. Hear best practices for:
Selecting the most appropriate data warehousing solution for your organizational needs
Maintaining data integrity through the aggregation process
Consolidating data in a manner that is useable to frontline staff
12:40 pm - 1:25 pm Where are the Women in Data?
The war for talent and the thirst for skills is a significant “choke point” for virtually every data driven organization and yet fewer than one in five Data Scientists are women. Learn how progressive companies are working to achieve greater diversity and to close the gender gap in their data & analytics teams.
Key talking points:
- Personal journeys, obstacles and achievements
- Sponsoring and mentoring women to create opportunities
- The future role of women in data
Kimberly ClarkManaging Director of Technology Governance & Controls Analytics
Charles Schwab & Co.
1:25 pm - 2:25 pm Networking Lunch
2:25 pm - 3:25 pm Practitioner Roundtables
Earlier in the Exchange, we collected your insights and challenges using Thoughtexchange. We identified the highest rated topic areas. During this session, you’ll have the opportunity to choose a topic and participate in a small group discussion. You will work in groups to develop an action plan for improvement.
3:10 pm - 3:40 pm Data Science As A Key Part Of Your Business Strategy To Drive Exponential & Sustainable Growth
Identifying the business problems that need to be fixed is a crucial piece of using data & analytics to drive revenue growth. The first step is to identify those issues from a business, not a technical perspective. Once those key problems have been identified then one can decide which are the right people, skills and tools needed to solve those problems. Only then will the initiatives yield results that are both exponential and sustainable.
This session will reveal:
• How to create the strategy from a business first perspective
• How to get leadership and cultural buy in to the value of solving key problems
• How to get funding by showing near term wins to support the long term strategy
Fernando MoreiraSenior Vice President, Global Insurance
3:40 pm - 4:10 pm Business Meetings
4:10 pm - 4:40 pm Business Meetings
4:40 pm - 5:10 pm Business Meetings
5:10 pm - 5:25 pm Networking Break
5:25 pm - 5:55 pm The Evolution of Risk Management at Capital One
As banking is undergoing its digital revolution with data, analytics and models to transform, risk management is a big part of it. Until recently digitization in banks has concentrated mostly on customer-facing use cases (such as online marketing) and the operations that support these (customer acquisition, customer management and servicing). Only recently have banks expanded their transformations into other part of the organization, including the risk function. This case study will demonstrate how Capital One captures, transforms and manages information from broad rich sets of data, automates risk management through developed data pipelines, and establishes new processes for feature explorations and model development life cycle.
This case study will reveal:
• how Capital One changed its overall risk culture
• how it created a more cohesive and well-managed data ecosystem
• how Capital One centralized the data and brought cost efficiency and productivity
Yuri BogdanovHead of Data Engineering and Analytics
Choose your topic